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Multi-Task Learning

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.

( Image credit: Cross-stitch Networks for Multi-task Learning )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1011–1020 of 3687 papers

Title	Date	Tasks	Status	Hype	Score
Context-Aware Embeddings for Automatic Art Analysis	Apr 10, 2019	Art AnalysisCross-Modal Retrieval	CodeCode Available	0	5
A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks	Nov 5, 2016	ChunkingMulti-Task Learning	CodeCode Available	0	5
Revisiting RCNN: On Awakening the Classification Power of Faster RCNN	Mar 19, 2018	ClassificationGeneral Classification	CodeCode Available	0	5
Emo2Vec: Learning Generalized Emotion Representation by Multi-task Training	Sep 12, 2018	Abusive LanguageClassification	CodeCode Available	0	5
HeroNet: A Hybrid Retrieval-Generation Network for Conversational Bots	Jan 29, 2023	Multi-Task LearningQuestion Answering	CodeCode Available	0	5
Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means Features	Nov 18, 2019	ClusteringData Augmentation	CodeCode Available	0	5
Emotion-Infused Models for Explainable Psychological Stress Detection	Jun 1, 2021	Language ModelingLanguage Modelling	CodeCode Available	0	5
Multi-Task Learning Framework for Emotion Recognition in-the-wild	Jul 19, 2022	Emotion RecognitionMulti-Task Learning	CodeCode Available	0	5
AnywhereDoor: Multi-Target Backdoor Attacks on Object Detection	Mar 9, 2025	Backdoor AttackMulti-Task Learning	CodeCode Available	0	5
Implicit Geometry and Interaction Embeddings Improve Few-Shot Molecular Property Prediction	Feb 4, 2023	Few-Shot LearningMolecular Docking	CodeCode Available	0	5

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All datasets QM9 Cityscapes test NYUv2 OMNIGLOT CelebA UTKFace wireframe dataset

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	PCGrad	∆m%	125.7	—	Unverified
2	CAGrad	∆m%	112.8	—	Unverified
3	IMTL-G	∆m%	77.2	—	Unverified
4	Nash-MTL	∆m%	62	—	Unverified
5	BayesAgg-MTL	∆m%	53.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SwinMTL	mIoU	76.41	—	Unverified
2	Nash-MTL	mIoU	75.41	—	Unverified
3	MultiObjectiveOptimization	mIoU	66.63	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SwinMTL	Mean IoU	58.14	—	Unverified
2	Nash-MTL	Mean IoU	40.13	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Gumbel-Matrix Routing	Average Accuracy	93.52	—	Unverified
2	Mixture-of-Experts	Average Accuracy	92.19	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MGDA-UB	Error	8.25	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BayesAgg-MTL	delta_m	-2.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	LETR	FH	83.3	—	Unverified